A variety of weighting procedures have been developed as generalizations of the parametric least-square-curve-fitting process. Hence it seems reasonable to apply weighting methods to nonparametric regression. In March of this year, we published a basic relationship which can be used to estimate the Fourier coefficients of a conditional density in terms of the sample bivariate trigonometric moments ("Trigonometric Maximum Likelihood Estimation and Application to the Analysis of Incomplete Survival Information" JASA 7, 365, p. 132-9). This relationship will enable us to apply our weighting procedures, which up to now have been only applied in the univariate case, to the problem of two-dimensional, nonparametric curve estimation. Early in the next project year we plan to conduct a series of simulation studies of the new weighting procedures. Besides checking the numerical accuracy of our computational methods we will use these trials to associate both particular weighting functions and parameters of these functions, with particular applications, e.g., sampling and curve fitting.